This is a full featured Moving Average
This one is for "The Bay" and for the community
The Bay wrote on groups.io :
"Allow for a moving average plot to be shifted forward or backward a selected number of
bars."
Indicator settings:
- Period (integer)
- Shift (can be a positive or negative integer)
- MA method (Simple, Exponential, Smoothed, Linear Weighted)
- Apply to (Close, Open, High, Low, Median Price (HL/2), Typical Price (HLC/3), Weighted
Close (HLCC/4))
- Current timeframe or Autodetect
- Bars back (integer)
Moving Average
The Moving Average Technical Indicator shows the mean instrument price value for
a certain period of time. When one calculates the moving average, one averages out
the instrument price for this time period. As the price changes, its moving average
either increases, or decreases.
There are four different types of moving averages: Simple (also referred to as
Arithmetic), Exponential, Smoothed and Linear Weighted. Moving averages may be
calculated for any sequential data set, including opening and closing prices, highest
and lowest prices, trading volume or any other indicators. It is often the case when
double moving averages are used.
The only thing where moving averages of different types diverge considerably from
each other, is when weight coefficients, which are assigned to the latest data, are
different. In case we are talking of simple moving average, all prices of the time
period in question, are equal in value. Exponential and Linear Weighted Moving
Averages attach more value to the latest prices.
The most common way to interpreting the price moving average is to compare its
dynamics to the price action. When the instrument price rises above its moving
average, a buy signal appears, if the price falls below its moving average, what we
have is a sell signal.
This trading system, which is based on the moving average, is not designed to provide
entrance into the market right in its lowest point, and its exit right on the peak. It
allows to act according to the following trend: to buy soon after the prices reach the
bottom, and to sell soon after the prices have reached their peak.
Moving averages may also be applied to indicators. That is where the interpretation of
indicator moving averages is similar to the interpretation of price moving averages: if
the indicator rises above its moving average, that means that the ascending indicator
movement is likely to continue: if the indicator falls below its moving average, this
means that it is likely to continue going downward.
Here are the types of moving averages on the chart:
- Simple Moving Average (SMA)
- Exponential Moving Average (EMA)
- Smoothed Moving Average (SMMA)
- Linear Weighted Moving Average (LWMA)
Calculation:Simple Moving Average (SMA)
Simple, in other words, arithmetical moving average is calculated by summing up the
prices of instrument closure over a certain number of single periods (for instance, 12
hours). This value is then divided by the number of such periods.
SMA = SUM(CLOSE, N) / N
Where:
N — is the number of calculation periods.
Exponential Moving Average (EMA)
Exponentially smoothed moving average is calculated by adding the moving average
of a certain share of the current closing price to the previous value. With
exponentially smoothed moving averages, the latest prices are of more value. P-
percent exponential moving average will look like:
EMA = (CLOSE(i) * P) + (EMA(i - 1) * (100 - P))
Where:
CLOSE(i) — the price of the current period closure;
EMA(i-1) — Exponentially Moving Average of the previous period closure;
P — the percentage of using the price value.
Smoothed Moving Average (SMMA)
The first value of this smoothed moving average is calculated as the simple moving
average (SMA):
SUM1 = SUM(CLOSE, N)
SMMA1 = SUM1/N
The second and succeeding moving averages are calculated according to this formula:
PREVSUM = SMMA(i - 1) * N
SMMA(i) = (PREVSUM - SMMA(i - 1) + CLOSE(i)) / N
Where:
SUM1 — is the total sum of closing prices for N periods;
PREVSUM — smoothed sum of previous bar;
SMMA1 — is the smoothed moving average of the first bar;
SMMA(i) — is the smoothed moving average of the current bar (except for the first
one);
CLOSE(i) — is the current closing price;
N — is the smoothing period.
The formula can be simplified as a result of arithmetic manipulations:
SMMA (i) = (SMMA(i - 1) * (N - 1) + CLOSE (i)) / N
Linear Weighted Moving Average (LWMA)
In the case of weighted moving average, the latest data is of more value than more
early data. Weighted moving average is calculated by multiplying each one of the
closing prices within the considered series, by a certain weight coefficient.
LWMA = SUM(Close(i)*i, N) / SUM(i, N)
Where:
SUM(i, N) — is the total sum of weight coefficients.